Partial shading on photovoltaic (PV) modules reduces the generated power of the PV system than the maximum power generated from each module separately. The shaded PV module acts as a load to unshaded ones which can lead to hot-spot. To alleviate the effect of partial shading, bypass diodes should be connected across each PV modules. Connecting several PV modules together produces multiple peaks (one global peak (GP) and multiple local peaks (LPs)) on partial shading conditions. Maximum power point tracker conventional techniques are designed to follow the GP but they stuck around LPs such as fuzzy logic controller (FLC). In this paper, modified particle swarm optimization (MPSO) using genetic algorism has been used to follow the GP under any operating conditions. MPSO has been studied and compared with the FLC technique to show the superiority of this technique under all operating conditions. Co-simulation between Matlab/Simulink and PSIM has been used to model the PV system under partial shading conditions. The simulation results show that the MPSO technique is more effective than FLC in following the GP. The generated power increases considerably with the MPSO than the FLC technique in shading conditions.

1.
B.
Kroposki
,
R.
Margolis
, and
D.
Ton
, “
Harnessing the sun
,”
IEEE Power Energy Mag.
7
(
3
),
22
33
(
2009
).
2.
M.
Hejri
and
H.
Mokhtari
, “
On the parameter extraction of a five-parameter double-diode model of photovoltaic cells and modules
,”
IEEE J. Photovoltaics
4
(
3
),
915
923
(
2014
).
3.
S. P. J. J.
Bikaneria
, “
Modelling and simulation of PV cell based on two-diode model
,”
Int. J. Recent Trends Eng. Technol.
11
,
589
594
(
2014
).
4.
N. M.
Shannan
,
N. Z.
Yahaya
, and
B.
Singh
, “
Two diode model for parameters extraction of PV module
,” in
IEEE Conference on Energy Conversion (CENCON)
,
2014
.
5.
K.
Ishaque
and
Z.
Salam
, “
A deterministic particle swarm optimization maximum power point tracker for photovoltaic system under partial shading condition
,”
IEEE Trans. Ind. Electron.
60
(
8
),
3195
3206
(
2013
).
6.
T.
Ma
,
H.
Yang
, and
L.
Lu
, “
Development of a model to simulate the performance characteristics of crystalline silicon photovoltaic modules/strings/arrays
,”
Sol. Energy
100
,
31
41
(
2014
).
7.
K.
Ishaque
,
Z.
Salam
, and
H.
Taheri
, “
Simple, fast and accurate two-diode model for photovoltaic modules
,”
Sol. Energy Mater. Sol. Cells
95
,
586
594
(
2011
).
8.
K.
Ishaque
,
Z.
Salam
,
H.
Taheri
, and
A.
Shamsudin
, “
A critical evaluation of EA computational methods for photovoltaic cell parameter extraction based on two diode model
,”
Sol. Energy
85
,
1768
1779
(
2011
).
9.
Y. J.
Wang
and
P. C.
Hsu
, “
Modelling of solar cells and modules using piece-wise linear parallel branches
,”
IET Renewable Power Gener.
5
(
3
),
215
222
(
2011
).
10.
T. O.
Saetre
,
O. M.
Midtg˚arg
, and
G. H.
Yordanov
, “
A new analytical solar cell i-v curve model
,”
Renewable Energy
36
(
8
),
2171
2176
(
2011
).
11.
H.
Rezk
and
A. M.
Eltamaly
, “
A comprehensive comparison of different MPPT techniques for photovoltaic systems
,”
Sol. Energy
112
,
1
11
(
2015
).
12.
D.
Rossi
,
M.
Omana
,
D.
Giaffreda
, and
C.
Metra
, “
Modeling and detection of hotspot in shaded photovoltaic cells
,”
IEEE Trans. VLSI Syst.
23
(
6
),
1031
(
2014
).
13.
J.
Solórzano
and
M. A.
Egido
, “
Hot-spot mitigation in PV arrays with distributed MPPT (DMPPT)
,”
Sol. Energy
101
,
131
137
(
2014
).
14.
Q.
Zhang
,
Y. Z. X.
Sun
,
L.
Guo
, and
M.
Matsui
, “
Operation mode analysis for solving the partial shadow in a novel PV power generation system
,”
Power Electronics Conference (IPEC-Hiroshima 2014-ECCE-ASIA)
,
Hiroshima
.
15.
K.
Kim
, “
Hot spot detection and protection methods for photovoltaic systems
,” Ph.D. dissertation (
University of Illinois at Urbana-Champaign
,
2014
).
16.
A. M.
Eltamaly
,
A. I.
Alolah
, and
M. Y.
Abdulghany
, “
Digital implementation of general purpose fuzzy logic controller for photovoltaic maximum power point tracker
,” in
IEEE Speedam 2010
,
Pisa, Italy
,
2010
.
17.
J.
Łukasiewicz
, “
On three-valued logic
,”
Ruch Filozoficzny
5
,
170
171
(
1920
).
18.
L. A.
Zadeh
, “
Fuzzy sets and systems
,”
System Theory
(
Polytechnic Press
,
New York
,
1965
), pp.
29
39
.
19.
L. A.
Zadeh
, “
Fuzzy sets
,”
Inf. Control
8
(
3
),
338
353
(
1965
).
20.
M.
Boukens
and
A.
Boukabou
, “
PD with fuzzy compensator control of robot manipulators: Experimental study
,” in
3rd International Conference on Systems and Control (ICSC)
,
2013
.
21.
A. E.
Khateb
,
N. A.
Rahim
,
J.
Selvaraj
, and
M. N.
Uddin
, “
Fuzzy logic controller based SEPIC converter for maximum power point tracking
,”
IEEE Trans. Ind. Appl.
50
(
4
),
2349
(
2014
).
22.
S.
El Beid
and
S.
Doubabi
, “
DSP-based implementation of fuzzy output tracking control for a boost converter
,”
IEEE Trans. Ind. Electron.
61
(
1
),
196
209
(
2014
).
23.
R.
Tipsuwanpom
,
T.
Runghimmawan
,
S.
Intajag
, and
V.
Krongratana
, “
Fuzzy logic PID controller based on FPGA for process control
,” in
2004 IEEE International Symposium
,
2004
.
24.
A. M.
Eltamaly
, “
Modeling of fuzzy logic controller for photovoltaic maximum power point tracker
,” in
Solar Future 2010 Conference
,
Istanbul, Turkey
,
2010
.
25.
J.
Kennedy
and
R.
Eberhart
, “
Particle swarm optimization
,” in
Proceedings of IEEE International Conference on Neural Networks
,
1995
.
26.
M.
Miyatake
,
T.
Inada
,
I.
Hiratsuka
,
H.
Zhao
,
H.
Otsuka
, and
M.
Nakano
, “
Control characteristics of a fibonacci-search-based maximum power point tracker when a photovoltaic array is partially shaded
,” in
Power Electronics and Motion Control Conference, 2004
,
IPEMC
,
2004
.
27.
F.
Al-Obeidat
,
N.
Belacel
,
J. A.
Carretero
, and
P.
Mahanti
., “
Automatic parameter settings for the PROAFTN classifier using hybrid particle swarm optimization
,” in
Proceedings of the 23rd Canadian Conference on Artificial Intelligence
,
2010
.
28.
L.
Liu
and
C.
Liu
, “
A novel combined particle swarm optimization and genetic algorithm MPPT control method for multiple photovoltaic arrays at partial shading
,”
J. Energy Resour. Technol.
135
(
1
),
012002
(
2012
).
29.
M. R.
Rad
,
S. A.
Taher
, and
S.
Akbari
, “
A maximum power point tracker for photovoltaic arrays with particle swarm optimization technique in cooperation with fuzzy cognitive networks
,” in
NEEC 2010
,
2010
.
30.
K.
Ishaque
,
Z.
Salam
,
A.
Shamsudin
, and
M.
Amjad
, “
A direct control based maximum power point tracking method for photovoltaic system under partial shading conditions using particle swarm optimization algorithm
,”
Appl. Energy
99
,
414
422
(
2012
).
31.
Q.
Fu
and
N.
Tong
, “
A new PSO algorithm based on adaptive grouping for photovoltaic MPP prediction
,” in
2nd International Workshop on Intelligent Systems and Applications (ISA)
,
2010
.
32.
M. A.
Hassan
and
M. A.
Abido
, “
Optimal design of microgrids in autonomous and grid-connected modes using particle swarm optimization
,”
IEEE Trans. Power Electron.
26
(
3
),
755
769
(
2011
).
33.
Psim User Manual of PSIM computer Simulation, [Online], available at: http://powersimtech.com/wp-content/uploads/2015/05/PSIM-User-Manual.pdf (last accessed June,
2015
).
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